Marco-Christiani/zigrad
A deep learning framework built on an autograd engine with high level abstractions and low level control.
Zigrad helps AI researchers and engineers quickly transition their deep learning experiments into high-performance training systems. It takes early-stage deep learning model designs, often created with PyTorch-like interfaces, and outputs highly optimized, fast-running models ready for large-scale training. This tool is for AI practitioners and MLOps engineers who need to bridge the gap between rapid prototyping and production-ready performance.
186 stars.
Use this if you are developing deep learning models and need to optimize their performance for large-scale training without rebuilding your entire workflow or switching frameworks.
Not ideal if you need a comprehensive library of pre-built, optimized deep learning layers like convolutions or pooling, as these are still under development.
Stars
186
Forks
10
Language
Zig
License
LGPL-3.0
Category
Last pushed
Mar 11, 2026
Commits (30d)
0
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